varEst {StratifiedSampling} | R Documentation |
Estimator of the approximated variance for balanced sampling
Description
Estimator of the approximated variance for balanced sampling
Usage
varEst(X, strata, pik, s, y)
Arguments
X |
A matrix of size ( |
strata |
A vector of integers that represents the categories. |
pik |
A vector of inclusion probabilities. |
s |
A sample (vector of 0 and 1, if rejected or selected). |
y |
A variable of interest. |
Details
This function gives an estimator of the approximated variance of the Horvitz-Thompson total estimator presented by Hasler C. and Tillé Y. (2014).
Value
a scalar, the value of the estimated variance.
Author(s)
Raphaël Jauslin raphael.jauslin@unine.ch
References
Hasler, C. and Tillé, Y. (2014). Fast balanced sampling for highly stratified population. Computational Statistics and Data Analysis, 74:81-94.
See Also
Examples
N <- 1000
n <- 400
x1 <- rgamma(N,4,25)
x2 <- rgamma(N,4,25)
strata <- as.matrix(rep(1:40,each = 25)) # 25 strata
Xcat <- disjMatrix(strata)
pik <- rep(n/N,N)
X <- as.matrix(matrix(c(x1,x2),ncol = 2))
s <- stratifiedcube(X,strata,pik)
y <- 20*strata + rnorm(1000,120) # variable of interest
# y_ht <- sum(y[which(s==1)]/pik[which(s == 1)]) # Horvitz-Thompson estimator
# (sum(y_ht) - sum(y))^2 # true variance
varEst(X,strata,pik,s,y)
varApp(X,strata,pik,y)
[Package StratifiedSampling version 0.4.2 Index]